Activities data modeling in human internet of things platforms
A platform models and correlates physical activities based on users' interactions with a simple grip-metaphor design, enabling multi-dimensions actionable information to improve the health, performance and well-being of connected grip users within like-minded communities. For example, the platform captures multi-dimensional datasets generated from activities of each of a plurality of users on the online human internet of thing platform, where the activities include physical interactions with connected grips systems connected to the online human internet of thing platform. The platform then filters the captured multi-dimensional datasets into a plurality of categories and scores the filtered multi-dimensional data by the human internet of thing platform. Finally, the platform generates a multi-dimensional information modeling for each user based on the scored multi-dimensional data.
1. A method system for computing visualization differential of multi-dimensional information modeling, comprising:
capturing multi-dimensional datasets for respective physical efforts of a reference user and a non-reference user;
recording at least one reference video stream of the physical effort of the reference user with framerates synchronized with the captured multi-dimensional datasets of the physical effort of the reference user;
calculating a performance differential for the non-reference user's captured multi-dimensional datasets compared to the reference user's captured multi-dimensional datasets; and
adjusting a playback video framerate of the at least one reference video stream for the non-reference user based on the calculated performance differential.
2. The method of claim 1 , wherein calculating the performance differential comprises calculating a ratio based on conditional parameters.
3. The method of claim 1 , wherein recording the at least one reference video stream comprises recording video streams from multiple camera angles locked with framerates synchronized with the captured multi-dimensional datasets of the reference user.
4. The method of claim 3 , wherein the multi-dimensional datasets for the respective physical efforts of the non-reference user are captured using a dual-handled connected grip system integrated with an indoor bicycle.
5. The method of claim 3 , wherein the multi-dimensional datasets for the respective physical efforts of the non-reference user are captured using a dual-handled connected grip system integrated with an indoor rowing machine.
6. The method of claim 3 , wherein the multi-dimensional datasets for the respective physical efforts of the non-reference user are captured using a connected grip system integrated with fitness equipment selected from the group consisting of jump ropes, barbells, dumbbells, elastic bands, rowing machines, indoor bicycles, and road bicycles.